| Presentation | 2019-03-09 Learning method to recognize both illustration image and Real image using CNN Tomoya Takenaka, Koichi Watanabe, Seiji Tsuchiya, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In recent years, the development of robots has been carried out for making human life more convenient and more comfortable along with the development of artificial intelligence. As one of some movements of robot, there is a movement that the robot autonomously move and grab some objects which human needs. In order to realize such behavior, it is necessary for the robot to recognize the surrounding environment. However, in the surrounding environment there are objects other than real objects such as illustrations and paintings. When recognizing an image showing an illustration image / real object (hereinafter referred to as a real object image) with the current object recognition system, the recognition rate is about 76%. There is a problem that the recognition rate decreases. In this research, we aim to recognize both illustration images and real object images and verify the effectiveness of the learning model learning the illustration processed images by comparing with the conventional object recognition system. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Deep Learning / Object recognition / illustration image |
| Paper # | AI2018-53 |
| Date of Issue | 2019-03-02 (AI) |
| Conference Information | |
| Committee | AI / IPSJ-ICS / JSAI-KBS / JSAI-DOCMAS / JSAI-SAI |
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| Conference Date | 2019/3/7(4days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Tsunenori Mine(Kyushu Univ.) |
| Vice Chair | Daisuke Katagami(Tokyo Polytechnic Univ.) / Naoki Fukuta(Shizuoka Univ.) |
| Secretary | Daisuke Katagami(Ritsumeikan Univ.) / Naoki Fukuta(Univ. of Electro-Comm.) |
| Assistant | Yuko Sakurai(AIST) |
| Paper Information | |
| Registration To | Technical Committee on Artificial Intelligence and Knowledge-Based Processing / Special Interest Group on Intelligence and Complex Systems / Special Interest Group on Knowledge-Based Systems / Special Interest Group on Data Oriented Constructive Mining and Simulation / Special Interest Group on Society and Artificial Intelligence |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Learning method to recognize both illustration image and Real image using CNN |
| Sub Title (in English) | |
| Keyword(1) | Deep Learning |
| Keyword(2) | Object recognition |
| Keyword(3) | illustration image |
| 1st Author's Name | Tomoya Takenaka |
| 1st Author's Affiliation | Doshisha University(Doshisha) |
| 2nd Author's Name | Koichi Watanabe |
| 2nd Author's Affiliation | Doshisha University(Doshisha) |
| 3rd Author's Name | Seiji Tsuchiya |
| 3rd Author's Affiliation | Doshisha University(Doshisha) |
| Date | 2019-03-09 |
| Paper # | AI2018-53 |
| Volume (vol) | vol.118 |
| Number (no) | AI-492 |
| Page | pp.pp.1-5(AI), |
| #Pages | 5 |
| Date of Issue | 2019-03-02 (AI) |